Method of selecting receive antennas for MIMO systems

ABSTRACT

Aspects of the subject disclosure may include, for example, a device, process or software that determines an operation between a number of pairs of antennas of a set of antennas. A pair of antennas of the number of pairs of antennas is determined based on the operation. One antenna of the pair of antennas is eliminated from the set of antennas, which results in a reduced number of antennas remaining in the set of antennas. Each of the determining of the operation, the determining of the pair of antennas of the reduced number of antennas and the eliminating of the one antenna of the pair of antennas is repeated in response to the reduced number of antennas being greater than a predetermined number of antennas. Other embodiments are disclosed.

CROSS-REFERENCE TO RELATED APPLICATION(S)

This application is a continuation of and claims priority to U.S. patentapplication Ser. No. 14/252,467, filed Apr. 14, 2014 by Winters et al.,entitled “Method of Selecting Receive Antennas for MIMO Systems,” whichis a continuation of U.S. patent application Ser. No. 12/912,399 filedOct. 26, 2010 by Winters et al., entitled “Method of Selecting ReceiveAntennas for MIMO Systems,” (now U.S. Pat. No. 8,725,102), which is acontinuation of U.S. patent application Ser. No. 11/897,312 filed Aug.30, 2007 by Winters et al., entitled “Method of Selecting ReceiveAntennas for MIMO Systems,” (now U.S. Pat. No. 7,844,240), which is acontinuation of U.S. patent application Ser. No. 11/321,785 filed Dec.29, 2005 by Winters et al., entitled “Method of Selecting ReceiveAntennas for MIMO Systems,” (now U.S. Pat. No. 7,283,798), which is acontinuation of U.S. patent application Ser. No. 10/324,168 filed Dec.19, 2002 by Winters et al., entitled “Method of Selecting ReceiveAntennas for MIMO Systems,” (now U.S. Pat. No. 7,006,810). All sectionsof the aforementioned applications are incorporated herein by referencein their entirety.

FIELD OF THE DISCLOSURE

The present invention relates generally to systems having a plurality ofreceive antennas and, more particularly, to selecting a number ofreceive antennas from the plurality of receive antennas and processingsignals from the selected antennas.

BACKGROUND

Multiple Input Multiple Output (MIMO) systems are known to those ofordinary skill in the art. In a MIMO system, a stream of bits isdemultiplexed into a predetermined number of substreams. Each substreamis sent out over a different antenna. The signals get mixed through thewireless channel. Signal processing is applied to the signals at the setof receive antennas to unscramble the data. The unscrambled data streamsare multiplexed into the original high rate bit stream. In such systems,only a portion (e.g., if three substreams were used, only one third) ofthe spectrum, which would normally have been required is actually used.

Orthogonal Frequency Division Multiplexing (OFDM) is known to those ofordinary skill in the art. OFDM is a modulation technique useful fortransmitting large amounts of data over a radio wave. The OFDM techniquemodulates multiple carriers at different frequencies with the samesymbol rate such that the signals can be recovered without mutualinterference. The receiver acquires the signal, digitizes the acquiredsignal, and performs a Fast Fourier Transform (FFT) on the digitizedsignal to get back to the frequency domain. The modulation is thenrecovered on each carrier. This technique results in a large amount ofdata being transmitted in a relatively small bandwidth.

The MIMO systems provide high spectral efficiency. Multiple transmitmultiple receive antenna links increase the capacity of MIMO and MIMOOFDM systems. However, the implementation of high spectral efficiency isdifficult due to the complexity of the systems and the resultant highcosts.

It would, therefore, be desirable to provide a method of selectingreceive antennas for MIMO and MIMO OFDM systems, which reduces the costand complexity of the MIMO and MIMO OFDM receivers.

BRIEF DESCRIPTION OF THE DRAWINGS

Reference will now be made to the accompanying drawings, which are notnecessarily drawn to scale, and wherein:

FIG. 1 is a block diagram of a portion of a MIMO/MIMO OFDM system;

FIG. 2 is a flow chart of the present method;

FIG. 3 is a graph of outage probability in a MIMO OFDM with an SNR of 10db;

FIG. 4 is a graph of outage probability in a MIMO OFDM with an SNR of 30db; and

FIG. 5 is a graph of frame error rate (FER) in a MIMO OFDM.

DETAILED DESCRIPTION

Referring to FIG. 1, a prior art MIMO/MIMO OFDM system is shown. In theMIMO/MIMO OFDM system, a stream of bits 6 is demultiplexed bydemultiplexer/transmitter 1 into a predetermined number of substreams.Each substream is sent out over a different transmit antenna 2 a-2 f bydemultiplexer transmitter 1. The signals transmitted by the transmitantennas 2 a-2 f get mixed while traveling through the wireless channel5. The signals are received by receive antennas 3 a-3 f. The receivedsignals are coupled from the receive antennas 3 a-3 f toreceiver/multiplexer 4. Signal processing is applied to the signals atthe set of receive antennas to unscramble the data. The unscrambled datastreams are then demultiplexed into a high rate bit stream 7, which is acopy of the high rate bit stream 6.

As described above, MIMO and MIMO OFDM systems require relativelycomplex and expensive receivers. A method is presented by whichperforming receive antenna selection is provided, thereby reducing thecomplexity and cost of the receiver in MIMO and MIMO OFDM systems.

It is known that the incremental gain of additional receive antennas inMIMO and MIMO ODFM systems is negligible when the number of receiveantennas K is larger than the number of transmit antennas M. Hence,through receive antenna selection the reduced receiver complexity ispossible without significant loss in the capacity of the system. Thereare several selection methods based on the capacity or thesignal-to-interference and noise power ratio (SINR). These approachesrequire

$\quad\begin{pmatrix}K \\S\end{pmatrix}$computations of their own criteria, i.e., the capacity or the SINR,where K is the number of receive antennas and S represents the number ofselected antennas.

A MIMO system with K receive antennas and M transmit antennas will beused to describe the present invention. In slowly time-varying flatfading channel (also known as a Rayleigh fading channel) the receivedvector can be modeled as:y=x+w=Hs+w  Equation (1)

where y is the received vector with size K×1, x is the data component ofy, K by M matrix H represents the channel, M×1 vector s is thetransmitted vector with an identity correlation matrix and w is thenoise vector.

Each element in channel matrix H is an independent complex Gaussianrandom variable with a variance equal to unity. The transmitted vector sis normalized such that Tr{ss^(H)}=P where s^(H) is the hermitiantranspose of vector s, and P is the total transmitted power. The entriesof w are independent and identically distributed, and are defined byw(i)˜N(O, σ²) where N indicates normal distribution and σ² is the noisepower). The entries are independent over time and i.

S receive antennas are selected out of K antennas according to severalcriteria. By checking the capacity, S receive antennas are chosen out ofK antennas in a way that the capacity is maximized. Alternatively, byexamining the SINR, which is directly related to bit or symbol errorrate, the selection of S receive antennas out of K antennas can also beperformed.

In one embodiment, the receiver selects S antennas that allow amaximization of the capacity

$\begin{matrix}{C_{s} = {\underset{s{(\overset{\sim}{H})}}{\max\;\log_{2}}{{I_{s} + {\frac{\rho}{M}\overset{\sim}{H}{\overset{\sim}{H}}^{H}}}}}} & {{Equation}\mspace{14mu}(2)}\end{matrix}$where I_(s) is the S×S identity matrix,

$\rho = \frac{P}{\sigma^{2}}$is the mean signal-to-noise ratio (SNR) per receiver branch, reducedmatrix {tilde over (H)} is created by deleting K-S rows of channelmatrix H, and S({tilde over (H)}) represents the set of all possiblereduced matrices {tilde over (H)}.

Since there are

$\quad\begin{pmatrix}K \\S\end{pmatrix}$possible reduced channel matrices {tilde over (H)}, the capacity isevaluated as many times as

$\begin{pmatrix}K \\S\end{pmatrix}.$

The determinant in Equation (2) can be written as

$\begin{matrix}{{{I_{s} + {\frac{\rho}{M}\overset{\sim}{H}{\overset{\sim}{H}}^{H}}}} = {\prod\limits_{k = 1}^{r}\;\left( {1 + {\frac{\rho}{M}{\lambda_{k}}^{2}}} \right)}} & {{Equation}\mspace{14mu}(3)}\end{matrix}$where r is the rank of the reduced channel matrix {tilde over (H)} andλ_(k) is the singular value of reduced channel matrix {tilde over (H)}.The rank and the singular values are maximized for the maximum capacity.

There may be a case in which there are two rows of the channel matrix H,which are identical. Clearly only one of these rows should be selectedin reduced channel matrix {tilde over (H)}. Since these two rows carrythe same information, either row of these two rows can be deletedwithout losing any information about the transmitted vector. In additionif the rows have different powers (i.e., magnitude square of the norm ofthe row), then the lower power row can be deleted.

When there are no identical rows then the next two rows whosecorrelation is the next highest are chosen for the deletion. In thismanner the reduced channel matrix {tilde over (H)} whose rows aremaximally uncorrelated and have maximum powers are obtained. This leadsto several methods for determining the highest correlation rate amongthe set of receive antennas.

A first method (method 1) for determining the highest correlation rateis performed in accordance with the formula:

$\begin{matrix}{{{Corr}\left( {k,l} \right)} = {\left\langle {\frac{h_{k}}{{h_{k}}^{2}},h_{l}} \right\rangle }} & {{Equation}\mspace{14mu}(4)}\end{matrix}$

where X={1, 2, . . . K}, h_(k) is the k^(th) row of channel matrix H,h_(l) is the l^(th) row of channel matrix H, k≠l, and k, lεX.

The correlation rate is determined by taking the absolute value of theinner product of the two arguments. The result is the square root of thesum of the products of each value in the h vectors.

A second method (method 2) for determining the highest correlation rateis performed in accordance with the formula:

$\begin{matrix}{{{Corr}\left( {k,l} \right)} = {\left\langle {\frac{h_{k}}{h_{k}},h_{l}} \right\rangle }} & {{Equation}\mspace{14mu}(5)}\end{matrix}$

where X={1, 2, . . . K}, h_(k) is the k^(th) row of channel matrix H,h_(l) is the l^(th) row of channel matrix H, k≠l, and k, lεX.

Another method (method 3) for determining the highest correlation rateis performed in accordance with the formula:

$\begin{matrix}{{{Corr}\left( {k,l} \right)} = {\left\langle {\frac{h_{k}}{h_{k}},\frac{h_{l}}{h_{l}}} \right\rangle }} & {{Equation}\mspace{14mu}(6)}\end{matrix}$

where X={1, 2, . . . K}, h_(k) is the k^(th) row of channel matrix H,h_(l) is the l^(th) row of channel matrix H, k>l, and k, lεX.

Yet another method (method 4) for determining the highest correlationrate is performed in accordance with the formula:Corr(k,l)=|

h _(k) ,h

|  Equation (7)

where X={1, 2, . . . K}, h_(k) is the k^(th) row of channel matrix H,h_(l) is the l^(th) row of channel matrix H, k>l, and k, lεX.

Method 4 is the least complex method to implement. The above methods donot require the SNR value and are based mainly on the correlationE{y_(k),y_(l) ⁺} where E is the expected value of the inner product oftwo output vector y's average, of the sum of the products of each valuein y's.

As an alternative method when the SNR is available, the mutualinformation between received vector Y_(k) and received vector Y_(l) isused. The zero-valued mutual information means the received vector Y_(k)and the received vector Y_(l) carry totally different information. Thisoccurs when the corresponding channel vector h_(k) and h_(l) areorthogonal. The channel vector h_(k) is defined as the k-th row of thechannel matrix H. If the mutual information is maximum, the receivedvector y_(k) and the received vector y_(l) carry the same information sothat one of them can be deleted. The mutual information is defined asI(y _(k) ;y _(l))=H(y _(k))+H(y _(l))−H(y _(k) ,y _(l))  Equation (8)

In the MIMO system the mutual information can be written as

$\begin{matrix}{{I\left( {y_{k};y_{l}} \right)} = {\log\frac{\left( {{{h_{k}}^{2}\frac{\rho}{M}} + 1} \right)\left( {{{h_{l}}^{2}\frac{\rho}{M}} + 1} \right)}{{\left( {{{h_{k}}^{2}\frac{\rho}{M}} + 1} \right)\left( {{{h_{l}}^{2}\frac{\rho}{M}} + 1} \right)} - {{\left\langle {h_{k},h_{l}} \right\rangle }^{2}\frac{\rho^{2}}{M^{2}}}}}} & {{Equation}\mspace{14mu}(9)}\end{matrix}$

Since the mutual information is bounded as following0≦I(y _(k) ;y _(l))≦min(H(y _(k)),H(y _(l)))  Equation (10)the normalized mutual information is defined below as

$\begin{matrix}{{I_{0}\left( {y_{k};y_{l}} \right)} = \frac{I\left( {y_{k};y_{l}} \right)}{\min\left( {{H\left( y_{k} \right)},{H\left( y_{l} \right)}} \right)}} & {{Equation}\mspace{14mu}(11)}\end{matrix}$as a measure of how close the two random variables are. The entropycalculation of the received vector y_(k) requires both the signal andnoise power, whereas the mutual information needs the SNR only.

This can be overcome as follows. The scaling of receive vector y_(k) toc·y_(k), where the non-zero real number c is chosen in the way that thenoise variance is equal to one, will not normalize mutual information.The scaling does not change the mutual information while the entropy ofc·y_(k) becomes

$\begin{matrix}{{H\left( {c - y_{k}} \right)} = {{\log\left( {{c^{2}{h_{k}}^{2}\frac{P}{M}} + {c^{2}\sigma^{2}}} \right)} = {\log\left( {{{h_{k}}^{2}\frac{\rho}{M}} + 1} \right)}}} & {{Equation}\mspace{14mu}(12)}\end{matrix}$The normalized mutual information is redefined as

$\begin{matrix}{{I_{0}\left( {y_{k};y_{l}} \right)} = \frac{I\left( {{c \cdot y_{k}};{c \cdot y_{l}}} \right)}{\min\left( {{H\left( {c \cdot y_{k}} \right)},{H\left( {c \cdot y_{l}} \right)}} \right)}} & {{Equation}\mspace{14mu}(13)}\end{matrix}$Then, the normalized mutual information becomes

$\begin{matrix}{{I_{0}\left( {y_{k};y_{l}} \right)} = \frac{I\left( {y_{k};y_{l}} \right)}{\min\left( {{\log\left( {{{h_{k}}^{2}\frac{\rho}{M}} + 1} \right)},{\log\left( {{{h_{l}}^{2}\frac{\rho}{M}} + 1} \right)}} \right)}} & {{Equation}\mspace{14mu}(14)}\end{matrix}$

The procedure for calculating the normalized mutual information (method5) is done in accordance with the formula:I ₀(y _(k) ;y _(l))  Equation (15)

where X={1, 2, . . . K}, k>l, and k, lεX.

The mutual information based technique can also be applied to the datacomponent x_(k) in order to avoid requiring the SNR value. Then, themutual information between the data component x_(k) and the datacomponent x_(l) is

$\begin{matrix}{{I\left( {x_{k};x_{l}} \right)} = {\log{\frac{{h_{k}}^{2}{h_{l}}^{2}}{{{h_{k}}{h_{l}}^{2}} - {\left\langle {h_{k},h_{l}} \right\rangle }^{2}}.}}} & {{Equation}\mspace{14mu}(16)}\end{matrix}$

Similarly, the normalized mutual information is defined below as

$\begin{matrix}{{I_{0}\left( {x_{k};x_{l}} \right)} = {\frac{I\left( {{c \cdot x_{k}};{c \cdot x_{l}}} \right)}{\min\left( {{H\left( {c \cdot x_{k}} \right)},{H\left( {c \cdot x_{l}} \right)}} \right)} = \frac{I\left( {x_{k};x_{l}} \right)}{\min\left( {{\log{h_{k}}^{2}},{\log{h_{l}}^{2}}} \right)}}} & {{Equation}\mspace{14mu}(17)}\end{matrix}$The procedure for calculating the normalized mutual information (method6) is done in accordance with the formula:I ₀(x _(k) ;x _(l))  Equation (18)

where X={1, 2, . . . K}, k>l, and k, lεX.

Having described receiver antenna selection techniques with respect toMEMO systems, the following describes receiver selection techniques withrespect to MIMO OFDM systems.

In a MIMO OFDM system with N subcarriers, the channel matrix under timeinvariant channel can be modeled as a block diagonal matrix

$\begin{matrix}{H = \begin{bmatrix}{H(1)} & 0 & \ldots & 0 \\0 & {H(2)} & 0 & \vdots \\\vdots & 0 & \ddots & 0 \\0 & \ldots & 0 & {H(N)}\end{bmatrix}} & {{Equation}\mspace{14mu}(19)}\end{matrix}$where

${H(n)} = \begin{bmatrix}H_{11{(n)}} & H_{12{(n)}} & \ldots & {H_{1M}(n)} \\{H_{21}(n)} & {H_{22}(n)} & \ldots & {H_{2M}(n)} \\\vdots & \vdots & \ddots & \vdots \\{H_{K\; 1}(n)} & {H_{K\; 2}(n)} & \ldots & {H_{KM}(n)}\end{bmatrix}$represents the channel matrix between K receive and M transmit antennasat subcarrier n. The capacity becomes

$\begin{matrix}{C = {\sum\limits_{n = 1}^{N}{\log_{2}{{{I_{K} + {\frac{\rho}{M}{H(n)}{H^{H}(n)}}}}.}}}} & {{Equation}\mspace{14mu}(20)}\end{matrix}$

In the correlation based methods (methods 1-4 described above for a MIMOsystem) the correlation must now be averaged over the subcarriers toprovide the same function for a MIMO OFDM system. For example, thecorrelation formula used in method 1 for a MIMO system is modified toaccount for the subcarriers to become method 7, which is performed inaccordance with the formula:

$\begin{matrix}{{{Corr}\left( {k,l} \right)} = {{\sum\limits_{n = 1}^{N}\left\langle {\frac{h_{k}(n)}{{{h_{k}(n)}}^{2}},{h_{l}(n)}} \right\rangle}}} & {{Equation}\mspace{14mu}(21)}\end{matrix}$

where X={1, 2, . . . K}, h_(k)(n) is the k^(th) row of channel matrix atsubcarrier n H(n), k≠l, and k, lεX.

Similarly, the correlation formula used in method 2 for a MIMO system ismodified to become method 8 for a MIMO OFDM system, which is performedin accordance with the formula:

$\begin{matrix}{{{Corr}\left( {k,l} \right)} = {{\sum\limits_{n = 1}^{N}\left\langle {\frac{h_{k}(n)}{{h_{k}(n)}},{h_{l}(n)}} \right\rangle}}} & {{Equation}\mspace{14mu}(21)}\end{matrix}$

where X={1, 2, . . . K}, h_(k)(n) is the k^(th) row of channel matrix atsubcarrier n H(n), k≠l, and k, lεX.

The correlation formula used in method 3 for a MIM system is replacedwith method 9 for a MIMO OFDM system, which is performed in accordancewith the formula:

$\begin{matrix}{{{Corr}\left( {k,l} \right)} = {{\sum\limits_{n = 1}^{N}\left\langle {\frac{h_{k}(n)}{{h_{k}(n)}},\frac{h_{l}(n)}{{h_{l}(n)}}} \right\rangle}}} & {{Equation}\mspace{14mu}(23)}\end{matrix}$

where X={1, 2, . . . K}, h_(k)(n) is the k^(th) row of channel matrix atsubcarrier n H(n), k≠l, and k, lεX.

The correlation formula used in method 4 for a MIMO system is replacedwith method 10 for a MIMO OFDM system, which is performed in accordancewith the formula:

$\begin{matrix}{{{Corr}\left( {k,l} \right)} = {{\sum\limits_{n = 1}^{N}\left\langle {{h_{k}(n)},{h_{l}(n)}} \right\rangle}}} & {{Equation}\mspace{14mu}(24)}\end{matrix}$

where X={1, 2, . . . K}, h_(k)(n) is the k^(th) row of channel matrix atsubcarrier n H(n), k≠l, and k, lεX.

Defining the received vector at the k-th receive antenna asy_(k)=[y_(k)(1) y_(k)(2) . . . y_(k)(N)]^(T) where y_(k)(n) is the k-threceive antenna output at the n-th subcarrier, the mutual information inthe MIMO OFDM system becomesI(y _(k) ;y _(l))=H(y _(l))−H(y _(k) ,y _(l))  Equation (25)The block diagonal property of the MIMO OFDM channel matrix defines themutual information to be

$\begin{matrix}{{I\left( {y_{k};y_{l}} \right)} = {{\sum\limits_{n = 1}^{N}{H\left( {y_{k}(n)} \right)}} + {H\left( {y_{l}(n)} \right)} - {H\left( {{y_{k}(n)},{y_{l}(n)}} \right)}}} & {{Equation}\mspace{14mu}(26)}\end{matrix}$Hence, the mutual information-based techniques used in the MIMO systemsare modified to use the following normalized mutual information and totake into account the subcarrier n. Method 5 for a MIMO system isreplaced by method 11 for a MIMO OFDM system wherein:

$\begin{matrix}{{I_{0}\left( {y_{k};y_{l}} \right)} = \frac{\sum\limits_{n}{I\left( {{y_{k}(n)};{y_{l}(n)}} \right)}}{\min\left( {{\sum\limits_{n}{H\left( {c \cdot {y_{k}(n)}} \right)}},{\sum\limits_{n}{H\left( {c \cdot {y_{l}(n)}} \right)}}} \right)}} & {{Equation}\mspace{14mu}(27)}\end{matrix}$where y_(k) is the k-th receive vector at subcarrier n, y_(l) is thel-th receive vector at subcarrier n, c is a constant, H is a channelmatrix, k>l, and k, lεX.

Similarly, method 6 for a MIMO system is replaced by method 12 for aMIMO OFDM system, which is performed in accordance with the formula:

$\begin{matrix}{{I_{0}\left( {x_{k};x_{l}} \right)} = \frac{\sum\limits_{n}{I\left( {{x_{k}(n)};{x_{l}(n)}} \right)}}{\min\left( {{\sum\limits_{n}{H\left( {c \cdot {x_{k}(n)}} \right)}},{\sum\limits_{n}{H\left( {c \cdot {x_{l}(n)}} \right)}}} \right)}} & {{Equation}\mspace{14mu}(28)}\end{matrix}$

where y_(k) is the k-th receive vector at subcarrier n, y_(l) is thel-th receive vector at subcarrier n, c is a constant, H is a channelmatrix, k>l, and k, lεX.

Referring now to FIG. 2, a flow chart of the presently disclosed methodis depicted. The rectangular elements are herein denoted “processingblocks” and represent computer software instructions or groups ofinstructions. The diamond shaped elements, are herein denoted “decisionblocks,” represent computer software instructions, or groups ofinstructions, which affect the execution of the computer softwareinstructions represented by the processing blocks.

Alternatively, the processing and decision blocks represent stepsperformed by functionally equivalent circuits such as a digital signalprocessor circuit or an application specific integrated circuit (ASIC).The flow diagrams do not depict the syntax of any particular programminglanguage. Rather, the flow diagrams illustrate the functionalinformation one of ordinary skill in the art requires to fabricatecircuits or to generate computer software to perform the processingrequired in accordance with the present invention. It should be notedthat many routine program elements, such as initialization of loops andvariables and the use of temporary variables are not shown. It will beappreciated by those of ordinary skill in the art that unless otherwiseindicated herein, the particular sequence of steps described isillustrative only and can be varied without departing from the spirit ofthe invention. Thus, unless otherwise stated the steps described beloware unordered meaning that, when possible, the steps can be performed inany convenient or desirable order.

The process starts at step 10 wherein a set of receive antennas of aMIMO or MIMO OFDM receiver are identified. In the present example, theset of receive antennas comprise six antennas referred to as antenna1-antenna 6 respectively. While a set of six receive antennas are usedin this example, it should be appreciated that any number of receiveantennas could be used.

The process then proceeds to step 20 where a determination is made as tothe number of antennas to be used. For example, if the MIMO or MIMO OFDMreceiver has a set of six receive antennas, it may be desirable to onlyprocess signals from two of the six antennas. While only two of sixreceive antennas are used in this example, it should be appreciated thatany number of receive antennas could be used.

At step 30 an operation is executed for each antenna of the set ofreceive antennas. The operation may relate to determining the amount ofcorrelation between each antenna, which each other antenna of the set,or determining an amount of mutual information between antennas of theset.

At step 40 the two antennas, which yielded the maximum results of theoperation performed in step 30 are selected. In the present example, ifa correlation operation was performed and it turned out that antennas 4and 6 were the most closely correlated pair, than these two antennas areselected.

Following step 40, step 50 is executed wherein one of the two antennas(antenna 4, antenna 6) is deleted from the set of receive antennas.Therefore, either antenna 4 or antenna 6 is deleted from the set ofreceive antennas. Thus, initially the set of receive antennas includedantennas 1-6, and antenna 4 is deleted, leaving five remaining antennasin the set of receive antennas (antennas 1-3 and 5-6).

At step 60 a determination is made as to whether the remaining set ofantennas has the desired number of antennas left in the set. In thisinstance five antennas are remaining, while it is desired to have onlytwo remaining, so steps 40 and 50 are executed again. Each iteration ofsteps 40 and 50 result in another antenna being removed from the set ofreceive antennas. Steps 40 and 50 are repeated until there are only twoantennas remaining in the set of receive antennas. Once the desirednumber of antennas is left in the set of receive antennas, step 70 isexecuted.

At step 70, the antennas remaining in the set of receive antennas areused, and signals from these antennas are processed. The method thenends at step 80.

Referring now to FIGS. 3 and 4, the outage probability of each disclosedmethod in a MIMO OFDM system under frequency selective Rayleigh fadingchannel is shown. The number of subcarriers is 64. The maximum delayspread (T_(d)) is ¼ of the symbol duration and the r.m.s. delay spread(T_(d)) is assumed to be ¼ of the maximum delay spread with anexponential power distribution. The number of transmit and receiveantennas is 2 and 6, respectively. FIG. 3 uses an SNR of 10 db, whileFIG. 4 uses a SNR value of 30 db. Each method selects 2 out of 6 receiveantennas. For FIG. 3, the best selection is shown by line 210, and theworst selection is shown by line 220. The selection using methods 7-12are shown by lines 230, 240, 250, 260, 270 and 280 respectively. ForFIG. 4, the best selection is shown by line 310, and the worst selectionis shown by line 320. The selection using methods 7-12 are shown bylines 330, 340, 350, 360, 370 and 380 respectively. Among fast methodsthe mutual information based methods (methods 11 and 12) outperform thecorrelation-based methods (methods 7-10).

The FER (frame error rate) is shown in FIG. 5 when the bandwidthefficiency is 10 bits/sec/Hz. The worst selection has 3 dB loss at 10e.sup.−3 FER. Method 11 (line 470) has less than 0.5 dB loss while thecorrelation based methods (methods 7-10, designated by lines 430, 440,450 and 460 respectively) exhibit from 1 to 1.5 dB loss. The performanceof the fast method 12 (line 480) is comparable to or even better thanthat of the method 11 (line 470) at high FER while at low FER the method12 (line 480) has similar performance with the correlation based methods(not shown). Method 12 (line 480) has good performance overall while itdoes not require the SNR value as in the correlation based methods.

A method of performing receive antenna selection for MIMO and MIMO OFDMsystems has been described. The method executes a determinationoperation for a set of receive antennas, determines a maximum result ofthe determination operation for two of the antennas, eliminates one ofthe two antennas from the set of antennas, and repeats the determinationand elimination process until only a predetermined number of antennasremain in the set. The signals from these remaining antennas are thenprocessed. The present invention reduces receiver complexity and cost.

Having described preferred embodiments of the invention it will nowbecome apparent to those of ordinary skill in the art that otherembodiments incorporating these concepts may be used. Additionally, thesoftware included as part of the invention may be embodied in a computerprogram product that includes a computer useable medium. For example,such a computer usable medium can include a readable memory device, suchas a hard drive device, a CD-ROM, a DVD-ROM, or a computer diskette,having computer readable program code segments stored thereon. Thecomputer readable medium can also include a communications link, eitheroptical, wired, or wireless, having program code segments carriedthereon as digital or analog signals. Accordingly, it is submitted thatthat the invention should not be limited to the described embodimentsbut rather should be limited only by the spirit and scope of theappended claims.

The Abstract of the Disclosure is provided with the understanding thatit will not be used to interpret or limit the scope or meaning of theclaims. In addition, in the foregoing Detailed Description, it can beseen that various features are grouped together in a single embodimentfor the purpose of streamlining the disclosure. This method ofdisclosure is not to be interpreted as reflecting an intention that theclaimed embodiments require more features than are expressly recited ineach claim. Rather, as the following claims reflect, inventive subjectmatter lies in less than all features of a single disclosed embodiment.Thus the following claims are hereby incorporated into the DetailedDescription, with each claim standing on its own as a separately claimedsubject matter.

What is claimed is:
 1. A method for managing antennas of amultiple-input-multiple-output (MIMO) orthogonal frequency divisionmultiplexing system, comprising: identifying, by a system comprising aprocessor, a predetermined number of receive antennas; determining, bythe system, an amount of mutual information between a plurality of pairsof receive antennas of a set of receive antennas; identifying, by thesystem, a pair of receive antennas of the plurality of pairs of receiveantennas to obtain an identified pair of receive antennas; eliminating,by the system, one receive antenna of the identified pair of receiveantennas from the set of receive antennas to obtain a reduced set ofreceive antennas; determining, by the system, a number of receiveantennas of the reduced set of receive antennas; and repeating, by thesystem, the determining of the amount of mutual information between theplurality of pairs of receive antennas of the reduced set of receiveantennas and the eliminating of the one receive antenna of theidentified pair of receive antennas from the reduced set of receiveantennas in response to the number of receive antennas remaining in theset of receive antennas being greater than the predetermined number ofreceive antennas.
 2. The method of claim 1, further comprising:determining, by the system, a receive entropy for each receive antennaof the pair of receive antennas; and determining, by the system, a lowentropy receive antenna of the pair of receive antennas, whereineliminating the receive antenna comprises removing the low entropyreceive antenna.
 3. The method of claim 1, wherein the determining ofthe amount of mutual information comprises executing a correlationoperation to obtain a plurality of correlation results based on rows ofa channel matrix associated with the set of receive antennas.
 4. Themethod of claim 3, wherein identifying a pair of receive antennascomprises identifying the pair of receive antenna having a greatestcorrelation of the plurality of correlation results.
 5. The method ofclaim 3, wherein each row of the channel matrix comprises a plurality ofsubcarriers, wherein executing of the correlation operations comprisesdetermining, by the system, a correlation for the MIMO orthogonalfrequency division multiplexing system, and wherein a plurality ofsubcarriers are subcarriers of the orthogonal frequency divisionmultiplexing system.
 6. The method of claim 3, wherein identifying thepair of receive antennas comprises determining one of an absolute valueof an inner product of a first row of the channel matrix divided by amagnitude square of a norm of the first row of the channel matrix and asecond row of the channel matrix, or an absolute value of an innerproduct of a normalized first row of the channel matrix and the secondrow of the channel matrix.
 7. The method of claim 3, wherein identifyingthe pair of receive antennas comprises determining one of an absolutevalue of an inner product of a normalized first row of the channelmatrix and a normalized second row of the channel matrix, or an absolutevalue of an inner product of the first row of the channel matrix and thesecond row of the channel matrix.
 8. The method of claim 1, wherein theidentifying of the pair of receive antennas comprises determining thepair of receive antennas having the amount of mutual information greaterthan other pairs of antennas of the plurality of pairs of receiveantennas of a set of receive antennas.
 9. A non-transitory,machine-readable storage medium, comprising executable instructionswhich, responsive to being executed by a processor of amultiple-input-multiple-output antenna system, cause the processor toperform operations comprising: determining an operation between aplurality of pairs of receive antennas of a set of receive antennas;identifying a pair of receive antennas of the plurality of pairs ofreceive antennas based on the operation to obtain an identified pair ofreceive antennas; eliminating one receive antenna of the identified pairof receive antennas from the set of receive antennas to obtain a reducedset of receive antennas; and repeating the determining of the operationbetween a plurality of receive antennas of the reduced set of receiveantennas, the identifying of the pair of receive antennas and theeliminating of the one receive antenna of the identified pair of receiveantennas in response to a number of receive antennas remaining in thereduced set of receive antennas being more than a predetermined numberof receive antennas.
 10. The non-transitory, machine-readable storagemedium of claim 9, wherein the operation comprises executing acorrelation operation to obtain a plurality of correlation results basedon rows of a channel matrix associated with the set of receive antennas.11. The non-transitory, machine-readable storage medium of claim 10,wherein the identifying of the pair of receive antennas comprisesidentifying the pair of receive antenna having a greatest correlation ofthe plurality of correlation results.
 12. The non-transitory,machine-readable storage medium of claim 10, wherein the identifying ofthe pair of receive antennas comprises identifying the pair of receiveantennas having a greatest correlation of the plurality of correlations.13. The non-transitory, machine-readable medium of claim 10, wherein theidentifying of the pair of receive antennas comprises determining one ofan absolute value of an inner product of a first row of the channelmatrix divided by a magnitude square of a norm of the first row of thechannel matrix and a second row of the channel matrix, or an absolutevalue of an inner product of a normalized first row of the channelmatrix and the second row of the channel matrix.
 14. The non-transitory,machine-readable storage medium of claim 10, wherein identifying thepair of receive antennas having a greatest correlation from the set ofreceive antennas comprises determining one of an absolute value of aninner product of a normalized first row of the channel matrix and anormalized second row of the channel matrix, or an absolute value of aninner product of the first row of the channel matrix and the second rowof the channel matrix.
 15. The non-transitory, machine-readable storagemedium of claim 9, wherein the operation comprises determining an amountof mutual information between a plurality of pairs of receive antennasof a set of receive antennas.
 16. The non-transitory, machine-readablemedium of claim 15, wherein the identifying of the pair of receiveantennas comprises determining the pair of receive antennas having theamount of mutual information greater than other pairs of antennas of theplurality of pairs of receive antennas of a set of receive antennas. 17.A multiple-input-multiple-output antenna system comprising: a memorythat stores executable instructions; and a processor coupled to thememory, wherein the processor, responsive to executing the instructions,facilitates performance of operations comprising: determining anoperation between a plurality of pairs of antennas of a set of antennas;determining a pair of antennas of the plurality of pairs of antennasbased on the operation; eliminating one antenna of the pair of antennasfrom the set of antennas, resulting in a reduced number of antennasremaining in the set of antennas; and repeating the determining of theoperation, the determining of the pair of antennas of the reduced numberof antennas and the eliminating of the one antenna of the pair ofantennas in response to the reduced number of antennas being greaterthan a predetermined number of antennas.
 18. The system of claim 17,wherein the operations further comprise: determining an entropy for eachantenna of the pair of antennas; and determining a low entropy antennaof the pair of antennas, wherein the eliminating of the one antennacomprises removing the low entropy antenna.
 19. The system of claim 17,wherein the operation between the plurality of pairs of antennascomprises determining a plurality of correlations between different rowsof a channel matrix associated with the set of antennas.
 20. The systemof claim 19, wherein identifying of the pair of antennas comprisingidentifying the pair of antennas having a greatest correlation of theplurality of correlations.